Organspecific stratification of radioepidemiological risk in urban radiological dispersion under atmospheric and demographic variation.

Authors

Alvaro Barros, Jakler Nichele, Andre Tavares, Edson Andrade

Published in

International journal of radiation biology. Pages 1-9. Aug 07, 2026. Epub Aug 07, 2026.

Abstract

Cancer risk associated with radionuclide exposure in urban radiological dispersal events varies by target organ, sex, and age at exposure, so whole-body average dose metrics underestimate the heterogeneity of individual risk.
This study quantified organ-specific excess relative risk (ERR) in a hypothetical urban radiological dispersal scenario, stratifying simultaneously by distance from the release point, Pasquill-Gifford (PG) atmospheric stability class, and demographic profile. The study population comprised 90 individuals distributed across three locations (0.3, 1.0, and 2.0 km) and three PG classes (D, E, and F), yielding nine independent combinations. Anatomical correspondence between the HotSpot nomenclature for 23 organs and the Biological Effects of Ionizing Radiation (BEIR) epidemiological categories was established through direct equivalence, functional grouping, and residual classification. For committed equivalent doses to organs below 100 mSv, the BEIR VII model was applied; above that operational threshold, an organ-specific extension based on BEIR V parameterizations was adopted. The Collective Risk Index (CRI) was synthesized through a demographically weighted index.
Under severe atmospheric stability (PG F), the 0.3 km location had a CRI of 146.519, equivalent to 91.3% of the total burden across all three locations. The female-to-male ratio exceeded unity in all scenarios, ranging from 1.109 to 1.639. Under extreme-dose conditions, non-monotonic reordering of aggregate risk by age group was observed.
Operational prioritization in urban radiological emergencies based solely on whole-body average quantities is insufficient: locations with comparable mean doses exhibit distinct risk hierarchies when anatomical resolution and demographic composition are explicitly incorporated into the decision model.

PMID:
42566282
Bibliographic data and abstract were imported from PubMed on 08 Aug 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.